Background:
Rapid detection, isolation and contact tracing of community COVID-19 cases are essential measures to limit the community spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to identify a parsimonious set of symptoms that jointly predict COVID-19 and whether predictive symptoms differ between B.1.1.7 (Alpha) lineage (predominating as of April 2021in the USA, UK and elsewhere) and wild type.
Methods and Findings:
We obtained throat and nose swabs with valid SARS-CoV-2 polymerase chain reaction (PCR) test results from 1,147,370 volunteers aged 5 years and above (6,450 positives) in the REal-time Assessment of Community Transmission-1 (REACT-1) study. This involved repeated community-based random surveys of prevalence in England (study rounds 2 to 8, June 2020 to January 2021, response rates 22%-27%). Participants were asked about symptoms occurring in the week prior to testing. Viral genome sequencing was carried out for PCR positive samples with N-gene cycle threshold value < 34 (N = 1,079) in round 8 (January 2021). In univariate analysis, all 26 surveyed symptoms were associated with PCR positivity compared with non-symptomatic people. Stability selection (1,000 penalized logistic regression models with 50% subsampling) among people reporting at least one symptom identified seven symptoms as jointly and positively predictive of PCR positivity in rounds 2–7 (June to December 2020): loss or change of sense of smell, loss or change of sense of taste, fever, new persistent cough, chills, appetite loss and muscle aches. The resulting model (rounds 2–7) predicted PCR positivity in round 8 with area under the curve (AUC) of 0.77. The same seven symptoms were selected as jointly predictive of B.1.1.7 infection in round 8, although comparing B.1.1.7 with wild type, new persistent cough and sore throat were more predictive of B.1.1.7 infection while loss or change of sense of smell was more predictive of the wild type. Main limitations of our study include i) potential participation bias despite random sampling of named individuals from the National Health Service register and weighting designed to achieve a representative sample of the population of England; and ii) the necessary reliance on self-reported symptoms, which may be prone to recall bias and may therefore lead to biased estimates of symptoms prevalence in England.
Conclusions:
Where testing capacity is limited, it is important to use tests in the most efficient way possible. We identified a set of seven symptoms that, when considered together, maximize detection of COVID-19 in the community, including infection with the B.1.1.7 lineage.